AlphaGo, an artificial intelligence machine o...

AlphaGo, an artificial intelligence machine outperformed Lee, which made the five-match　 score 4-1 ___________ AlphaGo.

A. in support of 　　　　　　 　 B. in favor of

C. in defense of　 　　　　　　 D. in need of

高二英语单项填空中等难度题查看答案及解析

Let us all raise a glass to AlphaGo and the advance of artificial　 intelligence. AlphaGo，

DeepMind’s Go-playing AI，just defeated the best Go-playing human，Lee Sedol. But as we drink to its success. we should also begin trying to understand what it means for the future.

The number of possible moves in a game of Go is so huge that. in order to win against a player like Lee. AlphaGo was designed to adopt a human—like style of gameplay by using a relatively recent development--deep learning. Deep learning uses large data sets，“machine learning”algorithms （计算程序） and deep neural networks to teach the AI how to perform a particular set of tasks. Rather than programming complex Go rules and strategies into AlphaGo，DeepMind designers taught AlphaGo to play the game by feeding it data based on typical Go moves. Then，AlphaGo played against itself, tirelessly learning from its own mistakes and improving its gameplay over time. The results speak for themselves.

Deep learning represents a shift in the relationship humans have with their technological creations. It results in AI that displays surprising and unpredictable behaviour. Commenting after his first loss，Lee described being shocked by an unconventional move he claimed no human would ever have made. Demis Hassabis. one of DeepMind's founders，echoed this comment：“We're very pleased that AlphaGo played some quite surprising and beautiful moves. ”

Unpredictability and surprises are—or can be—a good thing. They can indicate that a system is working well，perhaps better than the humans that came before it. Such is the case with AlphaGo. However，unpredictability also indicates a loss of human control. That Hassabis is surprised at his creation's behaviour suggests a lack of control in the design. And though some loss of control might be fine in the context of a game such as Go，it raises urgent questions elsewhere.

How much and what kind of control should we give up to AI machines? How should we design appropriate human control into AI that requires us to give up some of that very control? Is there some AI that we should just not develop if it means any loss of human control? How much of a say should corporations，governments，experts or citizens have in these matters? These important questions, and many others like them，have emerged in response，but remain unanswered. They require human，not human - like，solutions.

So as we drink to the milestone in AI, let's also drink to the understanding that the time to answer deeply human questions about deep learning and AI is now.

1.What contributes most to the unconventional move of AlphaGo in the game?

A. The capability of self-improvement.

B. The constant input of large data sets.

C. The installation of deep neutral networks.

D. The knowledge of Go rules and strategies.

2.A potential danger of Al is _____.

A. the loss of human control　　 B. the friendly relationship

C. the fierce competition　　 D. the lack of challenge

3.How should we deal with the unpredictability of AI?

A. We should stop AI machines from developing even further.

B. We should call on the government to solve these problems for us.

C. We should rely on ourselves and come up with effective solutions.

D. We should invent even more intelligent machines to solve everything.

4.What's the author’s attitude towards this remarkable advance in AI?

A. Supportive.　　 B. Optimistic.

C. Doubtful.　　 D. Cautious.

高二英语阅读理解中等难度题查看答案及解析

Let us all raise a glass to AlphaGo and the advance of artificial　 intelligence. AlphaGo，

DeepMind’s Go-playing AI，just defeated the best Go-playing human，Lee Sedol. But as we drink to its success. we should also begin trying to understand what it means for the future.

The number of possible moves in a game of Go is so huge that. in order to win against a player like Lee. AlphaGo was designed to adopt a human—like style of gameplay by using a relatively recent development--deep learning. Deep learning uses large data sets，“machine learning”algorithms （计算程序） and deep neural networks to teach the AI how to perform a particular set of tasks. Rather than programming complex Go rules and strategies into AlphaGo，DeepMind designers taught AlphaGo to play the game by feeding it data based on typical Go moves. Then，AlphaGo played against itself, tirelessly learning from its own mistakes and improving its gameplay over time. The results speak for themselves.

Deep learning represents a shift in the relationship humans have with their technological creations. It results in AI that displays surprising and unpredictable behaviour. Commenting after his first loss，Lee described being shocked by an unconventional move he claimed no human would ever have made. Demis Hassabis. one of DeepMind's founders，echoed this comment：“We're very pleased that AlphaGo played some quite surprising and beautiful moves. ”

Unpredictability and surprises are—or can be—a good thing. They can indicate that a system is working well，perhaps better than the humans that came before it. Such is the case with AlphaGo. However，unpredictability also indicates a loss of human control. That Hassabis is surprised at his creation's behaviour suggests a lack of control in the design. And though some loss of control might be fine in the context of a game such as Go，it raises urgent questions elsewhere.

How much and what kind of control should we give up to AI machines? How should we design appropriate human control into AI that requires us to give up some of that very control? Is there some AI that we should just not develop if it means any loss of human control? How much of a say should corporations，governments，experts or citizens have in these matters? These important questions, and many others like them，have emerged in response，but remain unanswered. They require human，not human - like，solutions.

So as we drink to the milestone in AI, let's also drink to the understanding that the time to answer deeply human questions about deep learning and AI is now.

1.What contributes most to the unconventional move of AlphaGo in the game?

A. The capability of self-improvement.

B. The constant input of large data sets.

C. The installation of deep neutral networks.

D. The knowledge of Go rules and strategies.

2.A potential danger of Al is _____.

A. the loss of human control　　 B. the friendly relationship

C. the fierce competition　　 D. the lack of challenge

3.How should we deal with the unpredictability of AI?

A. We should stop AI machines from developing even further.

B. We should call on the government to solve these problems for us.

C. We should rely on ourselves and come up with effective solutions.

D. We should invent even more intelligent machines to solve everything.

4.What's the author’s attitude towards this remarkable advance in AI?

A. Supportive.　　 B. Optimistic.

C. Doubtful.　　 D. Cautious.

高二英语阅读理解困难题查看答案及解析

Instant Expert: Artificial Intelligence

Like it or not, Artificial Intelligence (AI) is starting to influence your life. Machines that have learned how to perform a task-or a huge range of tasks-better than humans are proving to be an invaluable resource. Join our speakers on a journey through the fascinating world of AI and give your own intelligence and instant upgrade.

Speakers:

Michael Veale, Lecturer in digital rights and regulation at University College London

Nello Cristianini, Professor of Artificial Intelligence at the University of Bristol

Lydia Nicholls, Researcher and writer

Helmut Hauser, Senior Lecturer in Robotics at the University of Bristol

Aleksandra Berditchevskaia, Nesta Senior Researcher at the Center for Collective Intelligence

Benefits of attending:

Become an expert one day

Open your mind, be inspired

What's included in your ticket:

In depth talks from leading AI researchers

Ask-an-expert Question Time session

Sandwich lunch, plus morning and afternoon refreshments

Exclusive Instant Expert certificate

Exclusive New Scientist subscription deal

Book information:

The event will be held in the Knowledge Center Auditorium, the British Library

Doors will be open at 9:15 am, with talks starting at 10 am as sharp. The event will finish at 5pm.

The schedule/exact running order for the day will be confirmed closed to the event, and will

be emailed to all ticket holders.

Should you require details about disabled access, please contact us at: live@newscientist.com.

Tickets:

Early bird: Save ￡ 20

Standard ticket:￡ 149

Student ticket:￡　 99-Limited Availability

1.The attraction of the event lies in the fact that it_

A.Provides three hot meals

B.gifts one copy of Lydia Nicholls' book

C.gives magazine subscribers free services

D.arranges particular interaction with experts

2.How much should a farther pay if he buys tickets for himself and his 15-year-old daughter?

A.￡ 119 B.￡ 169

C.￡ 288 D.￡ 248

3.The purpose of the passage is to

A.try to persuade us to enjoy AI

B.tell us about the influence of Al

C.attract us to join in an event of AI

D.inform us of the information about AI

高二英语阅读理解中等难度题查看答案及解析

Scientists at the University of Oxford have developed new artificial intelligence software to recognize the faces of chimpanzees in the wild. The new software will allow researchers to significantly cut back on time and resources spent analyzing video footage.

“For species like chimpanzees, which have complex social lives and live for many years, recording their behavior from short-term field research can only tell us so much.” says Dan Schofield, researcher and DPhil student at Oxford University’s Primate Models Lab. “By using the power of machine learning to unlock large video footage, it makes it feasible to measure behavior over the long term. Observing how the social lives of a group change over several generations become possible as well.”

The computer model was trained using over 10 million images from Kyoto University’s Primate Research Institute (PRI) video footage of wild chimpanzees in West Africa. The new software is the first to recognize individuals in a wide range of poses, performing with high accuracy in difficult conditions such as low lighting, poor image quality and movement blur (模糊).

“Access to this large video footage has allowed us to use cutting edge deep neural networks to train models at a scale that was previously not possible.” says Arsha Nagrani, co-author of the study and DPhil student in University of Oxford. “Additionally, our method differs from previous primate face recognition software in that it can be applied to raw video footage with limited manual intervention (人工干预) or pre-processing, saving hours of time and resources.”

The technology has potential for many uses, such as monitoring species for protection. Although the current application focused on chimpanzees, the software provided could be applied to other species, and help drive the adoption of artificial intelligence systems to solve a range of problems in the wildlife sciences.

“All our software is available open-source for the research community.” says Nagrani. “We hope that this will help researchers across other parts of the world apply the same cutting-edge techniques to their unique animal data sets. As a computer vision researcher, it is extremely satisfying to see these methods applied to solve real, challenging biodiversity (生物多样性) problems.”

“With an increasing biodiversity crisis and many of the world’s ecosystems under threat, the ability to closely monitor different species and populations using systems will be important for protection efforts, as well as animal behavior research.” adds Schofield. “Interdisciplinary cooperation like this have huge potential to make an impact, by finding solutions for old problems, and asking biological questions which were previously not available on a large scale.”

1.What’s the function of the new artificial intelligence software?

A.Analyzing video footage in difficult conditions.

B.Recognizing the faces of chimpanzees in the wild.

C.Cutting edge deep neural networks to train models at a scale.

D.Saving hours of time and resources without manual intervention.

2.What does the underlined word “feasible” in Paragraph 2 probably mean?

A.possible B.important

C.natural D.official

3.From the passage, we know that the artificial intelligence software could ________.

A.recognize individuals but not clearly

B.save time and resources only

C.help to protect different species

D.hardly solve biodiversity problems

4.What is the main purpose of the passage?

A.To introduce a new software.

B.To explain a measure.

C.To assess a project.

D.To describe a procedure.

高二英语阅读理解中等难度题查看答案及解析

Artificial intelligence keeps defeating human, it is making countless victories against human in different fields of life and trying to push human to the corner.

Google’s DeepMind has defeated the world’s number one player Ke Jie. Human brain somehow has been replaced by a machine and scientists are working very hard on developing a human brain by implanting a chip and connecting it to the thick neuron that connects the two hemispheres of the brain. Well, who doesn’t want to get his brain upgraded to be as smart as the brain of Albert Einstein or Charles Darwin?

Humans will probably one day invent a brain that can be implanted in the human skull and reprogram all the human thoughts, but this invention doesn’t seems to be happening in the foreseeable future since human brain took millions of years to evolve. Some scientists believe that human will defeat death in the next twenty hundred years but they can’t really predict how long it’s going to take to develop a human brain that can completely replace the natural brain.

Despite of this accomplishment in the field of artificial intelligence, it couldn’t crease people from believing that science can’t stand alone. For instance, AI can imitate human brain and most of the time outperforms it, but there are still a lot of hidden secrets. AI outsmarted Ke Jie has consciousness unlike the AI, Ke Jie felt sad when he was defeated and buried his face in his hands but the AI didn’t feel happy and celebrate his victory.

The computer of 1960 is the same as the computer of 2017 in terms of consciousness, there is no signs so far telling us that there is an algorithm(运算)that can make a conscious computer and decipher (译解) its feelings. We can predict what the future will look like according to the past, especially from scientific point of view but the development of human brain seems unpredictable and unknown.

1.What is the possible meaning of the underlined word “neuron” in Para. 2?

A. The tube through which blood flows in your brain.

B. The kind of cell that carries information.

C. The soft fatty substance in the hollow center of bones.

D. The bony part of one’s head which encloses his/her brain.

2.What is Paragraph 3 mainly about?

A. It took millions of years for human brain to evolve.

B. Humans wish to get their brains upgraded to be as smart as possible.

C. Humans will probably invent a brain that can reprogram all the human thoughts.

D. It is hard to develop a human brain that can completely replace the natural brain.

3.“Ke Jie felt sad when he was defeated” is mentioned in Para. 4 to ________.

A. show that the AI has no human emotions

B. explain that AlphaGo is virtually unbeatable in the board game

C. tell us the accomplishment in the field of artificial intelligence

D. analyze Ke Jie’s psychological characteristics when playing the game

4.What can be the best title for the passage?

A. World Top Go Player Ke Jie Challenges AlphaGo

B. AlphaGo Teaches To use AI To benefit Humans

C. Google AI Defeats Human Go Champion

D. AI Can Imitate Human Brain And Most Of the Time Outperforms It

高二英语阅读理解中等难度题查看答案及解析

Learning, Fast and Deep

Over the past five years researchers in artificial intelligence have become the rock stars of the technology world. A branch of AI known as deep learning, which uses neural(神经的) networks to scan through large volumes of data looking for patterns, has proven so useful that skilled practitioners can command high six-figure salaries to build software for Amazon, Apple, Facebook and Google.

The standard route into these jobs has been a PhD in computer science from one of America’s top universities. Earning one takes years and requires a personality suited to academia, which is rare among more normal folk.

That is changing.

Last month fast.ai, a non-profit education organization based in San Francisco, kicked off the third year of its course in deep learning. Since its foundation it has attracted more than 100,000 students around the globe from India to Nigeria. The course and others like it, come with a simple idea: there is no need to spend years obtaining a PhD in order to practise deep learning. Creating software that learns can be taught as a craft, not as a high intellectual pursuit to be undertaken only in an ivory tower. Fast.ai’s course can be completed in just seven weeks.

To make it accessible to anyone who wants to learn how to build AI software is the aim of Jeremy Howard, who founded fast.ai with Rachel Thomas, a mathematician. He says school mathematics is sufficient. “No. Greek. Letters,” Mr. Howard intones, pounding the table with his fist for punctuation.

Some experts worry that this will serve only to create a flood of unreliable AI systems which will be useless at best and dangerous at worst. In the earliest days of the Internet, only a select few nerds, namely computerholics with specific skills, could build applications. Not many people used them. Then the invention of the World Wide Web led to an explosion of web pages, both good and bad. But it was only by opening up to all that the Internet gave birth to online shopping, instant global communications and search. If Mr. Howard and others have their way, making the development of AI software easier will bring forth a new crop of fruit of a different kind.

1.What can we learn about deep learning?

A.It replaces artificial intelligence.

B.It attracts rock stars to practice.

C.It scans patterns for large companies.

D.It helps technicians to create software.

2.Fast.ai is an organization that __________________.

A.ensures one to obtain a PhD B.teaches craft in ivory tower

C.offers a course in deep learning D.requires weeks to apply

3.The underlined words “No. Greek. Letters”in Paragraph 5 means doing fast.ai course is _______.

A.easy B.difficult

C.interesting D.boring

4.It can be inferred from the last paragraph that _______.

A.it is quite reliable for anyone to grasp artificial intelligence

B.the Internet has brought forth a flood of useless AI systems

C.opening up to all leads to instant global search and online shopping

D.simplifying software development may result in unexpected outcomes

高二英语阅读理解中等难度题查看答案及解析

Many leading AI researchers think that in a matter of decades, artificial intelligence will be able to do not merely some of our jobs, but all of our jobs, forever transforming life on Earth.

The reason why many regard this as science fiction is that we've traditionally thought of intelligence as something mysterious that can only exist in biological organisms, especially humans. But such an idea is unscientific.

From my point of view as a physicist and AI researcher, intelligence is simply a certain kind of information-processing performed by elementary particles (基本粒子) moving around, and there is no law of physics that says one can't build machines more intelligent than us in all ways. This suggests that we've only seen the tip of the intelligence iceberg and that there is an amazing potential to unlock the full intelligence that is potential in nature and use it to help humanity.

If we get it right, the upside is huge. Since everything we love about civilization is the product of intelligence, amplifying (扩大) our own intelligence with AI has the potential to solve tomorrow's toughest problems. For example, why risk our loved ones dying in traffic accidents that self-driving cars could prevent or dying of cancers that AI might help us find cures for? Why not increase productivity through automation (自动化) and use AI to accelerate our research and development of affordable sustainable (可持续的) energy?

I'm optimistic that we can develop rapidly with advanced AI as long as we win the race between the growing power of our technology and the knowledge with which we manage it. But this requires giving up our outdated concept of learning form mistakes. That helped us win the race with less powerful technology: We messed up with fire and then invented fire extinguishers (灭火器), and we messed up with cars and then invented seat belts. However, it's an awful idea for more powerful technologies, such as nuclear weapons or superintelligent AI—where even a single mistake is unacceptable and we need to get things right the first time.

1.How do many people feel about leading AI researchers' predictions?

A.Worried. B.Curious. C.Doubtful. D.Disappointed.

2.What does the author think of intelligence?

A.We know little about it. B.It belongs to human beings.

C.It is too difficult to understand. D.We have nothing more to discover.

3.What does the underlined word “upside” in Paragraph 4 probably mean?

A.Cost. B.Risk. C.Quantity. D.Advantage.

4.What's important for us in the race between people and technology?

A.Learning from failure. B.Increasing our intelligence.

C.Avoiding making mistakes. D.Being more optimistic.

高二英语阅读理解中等难度题查看答案及解析

Rapid progress in artificial intelligence, also called AI, and the wide use of robots across different industries are causing the worry about the growth in joblessness. People have different opinions on this development, and they mainly have focused on what to do to make sure that robots don't steal jobs.

Bill Cates, for example, have called for taxing(对…征税)robots that take away jobs. This has led to disagreement from other leading figures, such as Larry Summers, who thinks that robots are job creators and that it is totally wrong. Another idea is to use a basic income for all-the ides that everyone receives the lowest income-to pay for influence of technological unemployment. This idea also causes disagreement.

However, jobs are not created or lost because of a single technology, but because of the business system designed to make use of the power of the technology.

We have seen a similar example in history, with recorded music in the last century. It wasn't the 1930s recording technology itself that affected the jobs of the live musicians. It was its connection with radio broadcasting，jukeboxes(自动唱机)and the way businesses operated that led to the job losses. Hotels, restaurants and bars replaced live musicians with jukeboxes. A single recording could be placed over and over without requiring the appearance of the musicians.

The early recording of music destroyed the jobs of some live musicians and made them earn less money than before. The social dissatisfaction was largely about monopoly power(垄断势力)and less about the technology itself.

Job creation or loss has to be considered with everything considered. This is the best explained by looking at the difference between recorded music in the last century and robots now.

1.What's people's main attention according to the first paragraph?

A.Artificial intelligence. B.The growing opportunities.

C.Not letting robots take away jobs. D.Stopping the wide use of robots.

2.What does the underlined word "it" in paragraph 2 refer to?

A.The idea of taxing robots. B.The belief that robots steal jobs.

C.Rapid progress in artificial intelligence. D.Disagreement between leading figures.

3.What can we know about Larry Summers?

A.He agrees with Bill Gates' opinion. B.He thinks robots can create jobs.

C.He supports the idea of taxing robots. D.He praises using a basic income for all

4.What can we infer from the last two paragraphs?

A.There will be more social dissatisfaction in the future.

B.Monopoly power is a terrible social phenomenon.

C.We should tell job creation or loss with full consideration.

D.Recorded music is completely different from robots.

高二英语阅读理解困难题查看答案及解析

Driverless cars are the best-known example of how artificial intelligence is influencing daily life in China, according to a new report on social attitudes toward AI technology that was released at Fudan University on May 17.

Based on the responses of 625 questionnaires made by Fudan University’s National Center for Cultural Innovation Research and the communication and data science laboratory, the report states that nearly 90 percent of the respondents are familiar with driverless cars, with over 67, percent having access to both positive and negative information on cars. About 62 percent of the respondents said they were willing to ride in driverless cars. Meanwhile, around 47 percent were supportive of unmanned vehicle road tests in the country. However, more than 30 percent of the respondents expressed their concerns about the safety of driverless cars.

If personal injuries or property loss are suffered in the event of an accident, 80.5 percent of the respondents said that the designers of the AI products should bear legal responsibility while 55.5 percent said that vehicle users should also shoulder the blame.

Smart cars with partial or fully autonomous functions are expected to account for 50 percent of new vehicles sold in China by 2020.According to the blueprint released by the National Development and Reform Commission in January, the country is aiming to become a global power in smart-car development and production by 2035.

“One cannot ignore the risks and ethics issues brought up by artificial intelligence technology,” said Sun Shaojing, director of the Communication and Data Science Laboratory of the National Center for Cultural Innovation Research at Fudan University, “Policies should be strengthened to ensure a balanced development of ethics and science, especially for some fast-growing applications like driverless cars.”

1.What do we know about the responses of 625 questionnaires?

A. More than half of the people surveyed were willing to ride in driverless cars.

B. Nearly 90% knew both positive and negative information on cars.

C. Unmanned vehicle road tests were hardly supported in the country.

D. Few people were concerned about the safety of driverless cars.

2.Who should take responsibility if an accident happened to a driverless car?

A. The designers of the AI products.

B. Both AI products designers and vehicle users.

C. Policy makers who regulate the use of driverless cars.

D. It hasn’t been decided yet.

3.What does the underlined word “autonomous” in Paragraph 4 probably mean?

A. high-tech　　 B. advanced

C. self-directed　　 D. useful

4.What do Sun Shaojing’s words suggest in the last paragraph?

A. We should mainly focus on the benefit that driverless cars bring to us.

B. Effective policies and rules are needed with appliances fast growing.

C. Risks and ethics issues brought up by AI cannot be avoided.

D. Driverless cars play a significant role in AI technology.

高二英语阅读理解中等难度题查看答案及解析